electricsheepafrica/africa-mauritania-current-situation-fewsnet-ipc-classification

Mauritania Current Situation FEWS NET Acute Food Insecurity Classifications Data

Publisher: FEWS NET · Source: HDX · License: cc-by · Updated: 2026-04-01

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Abstract

Mauritania Current Situation FEWS NET Acute Food Insecurity Classifications Data from 2011

Each row in this dataset represents first-level administrative unit observations. Temporal coverage is indicated by the projection_start, projection_end column(s). Geographic scope: MRT.

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Food security and nutrition
Unit of observation	First-level administrative unit observations
Rows (total)	1,715
Columns	40 (9 numeric, 23 categorical, 7 datetime)
Train split	1,372 rows
Test split	343 rows
Geographic scope	MRT
Publisher	FEWS NET
HDX last updated	2026-04-01

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Variables

Geographic — country (Mauritania), country_code (MR), fewsnet_region (West Africa), unit_type (fsc_admin_lhz, fsc_admin), specialization_type and 2 others.

Temporal — datacollectionperiod (range 159247.0–159328.0), reporting_date.

Outcome / Measurement — value (range 1.0–3.0).

Identifier / Metadata — source_organization (FEWS NET), source_document (Food Security Outlook, Mauritania), geographic_unit_full_name (Zouerate, Tiris Zemmour, Mauritania, Barkewol, Assaba, Mauritania, Bir Moghrein, Tiris Zemmour, Mauritania), geographic_unit_name (Agropastoralism, Nomadic pastoralist, Rainfed agriculture), fnid (MR2009C11103, MR2009C10301, MR2009C11101) and 8 others.

Other — geographic_group (Western Africa), classification_scale, is_allowing_for_assistance, projection_start, projection_end and 12 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-mauritania-current-situation-fewsnet-ipc-classification")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
source_organization	object	0.0%	FEWS NET
source_document	object	0.0%	Food Security Outlook, Mauritania
country	object	0.0%	Mauritania
country_code	object	0.0%	MR
geographic_group	object	0.0%	Western Africa
fewsnet_region	object	0.0%	West Africa
geographic_unit_full_name	object	0.0%	Zouerate, Tiris Zemmour, Mauritania, Barkewol, Assaba, Mauritania, Bir Moghrein, Tiris Zemmour, Mauritania
geographic_unit_name	object	0.0%	Agropastoralism, Nomadic pastoralist, Rainfed agriculture
unit_type	object	0.0%	fsc_admin_lhz, fsc_admin
fnid	object	0.0%	MR2009C11103, MR2009C10301, MR2009C11101
classification_scale	object	0.0%
scenario_name	object	0.0%
preference_rating	int64	0.0%	90.0 – 90.0 (mean 90.0)
is_allowing_for_assistance	bool	0.0%
projection_start	datetime64[ns]	0.0%
projection_end	datetime64[ns]	0.0%
status	object	0.0%
value	float64	0.0%	1.0 – 3.0 (mean 1.3347)
description	object	0.0%
id	int64	0.0%	24474855.0 – 24479997.0 (mean 24477426.0)
datacollectionperiod	int64	0.0%	159247.0 – 159328.0 (mean 159293.4694)
datacollection	int64	0.0%	168610.0 – 168637.0 (mean 168625.4898)
scenario	object	0.0%
geographic_unit	int64	0.0%	24509.0 – 24633.0 (mean 24568.9009)
datasourceorganization	int64	0.0%	1.0 – 1.0 (mean 1.0)
datasourcedocument	int64	0.0%	6605.0 – 6605.0 (mean 6605.0)
dataseries	int64	0.0%	6504441.0 – 6505244.0 (mean 6504768.435)
dataseries_name	object	0.0%
specialization_type	object	0.0%
dataseries_specialization_type	object	0.0%
data_usage_policy	object	0.0%
created	datetime64[ns]	0.0%
modified	datetime64[ns]	0.0%
status_changed	datetime64[ns]	0.0%
collection_status	object	0.0%
collection_status_changed	datetime64[ns]	0.0%
collection_schedule	object	0.0%
reporting_date	datetime64[ns]	0.0%
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
preference_rating	90.0	90.0	90.0	90.0
value	1.0	3.0	1.3347	1.0
id	24474855.0	24479997.0	24477426.0	24477426.0
datacollectionperiod	159247.0	159328.0	159293.4694	159298.0
datacollection	168610.0	168637.0	168625.4898	168627.0
geographic_unit	24509.0	24633.0	24568.9009	24568.0
datasourceorganization	1.0	1.0	1.0	1.0
datasourcedocument	6605.0	6605.0	6605.0	6605.0
dataseries	6504441.0	6505244.0	6504768.435	6504729.0

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Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. 3 column(s) with >80% missing values were removed: pct_phase3, pct_phase4, pct_phase5. 7 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

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Limitations

• Data originates from FEWS NET and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_mauritania_current_situation_fewsnet_ipc_classification,
  title     = {Mauritania Current Situation FEWS NET Acute Food Insecurity Classifications Data},
  author    = {FEWS NET},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/mauritania_current_situation_fewsnet_ipc_classification},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.